Physicochemical, Microbiological, Antioxidant and Sensory Characteristics of “Aguamiel” Microencapsulated by Spray Drying
Bibliographic record
Abstract
The aim of this work was to obtain powders of “aguamiel” (AM) (from Agave salmiana) by spray drying using maltodextrin (MD) and Arabic gum (AG) as encapsulates. Three microencapsulated powders were obtained: Powder 1 (P1, AM/MD), Powder 2 (P2, AM/AG/MD; AG:MD, 3:1) and Powder 3 (P3, AM/MD/AG; AG:MD, 1:3) from solutions with 20% (w/w) of solutes. Powders were evaluated according to their physicochemical, antioxidant, microbiological and sensory characteristics. Powders had averages of moisture content of 2.55 ± 0.24%, water activity of 0.34 ± 0.02, and particle size of 29.84 ± 1.4 μm. It was observed that the higher the concentration of Arabic gum, the darker the powders. The physicochemical and color properties of the rehydrated powders were similar to those of fresh “aguamiel”. The microbial load, during 95 days of storage, indicated no significant changes (p > 0.05) between the initial and final values in the three powders; the highest microbial load was observed in powder P3 (6.6x103 CFU/mL and 5.9x103 CFU/mL, initial and final loads, respectively). The content of phenolics in powders P1, P2 and P3 during storage were 212.40 ± 68.22, 350.51 ± 145.00, and 266.25 ± 89.93 mg Gallic acid equivalents/100 g, respectively; the antioxidant capacity was 1,207.13 ± 109.64, 1,172.17 ± 145.80, and 1,183.34 ± 65.17 mg Trolox equivalents/100 g, respectively. According to the sensory evaluation of the rehydrated powders, the better acceptance was obtained with the P3 powder, with better physicochemical and sensorial characteristics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".